• Journal of the Korean Society of Industry Convergence
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• v.23 no.5
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• pp.799-807
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• 2020

This paper deals with identification of probabilistic design using reliability based robust optimization in structure design of automatic salt collector. The thickness sizing variables of main structure member in the automatic salt collector were considered the random design variables including the uncertainty of corrosion that would be an inevitable hazardousness in the saltern work environment. The probabilistic constraint functions were selected from the strength performances of the automatic salt collector. The reliability based robust optimum design problem was formulated such that the random design variables were determined by minimizing the weight of the automatic salt collector subject to the probabilistic strength performance constraints evaluating from reliability analysis. Mean value reliability method and adaptive importance sampling method were applied to the reliability evaluation in the reliability based robust optimization. The three sigma level quality was considered robustness in side constraints. The probabilistic optimum design results according to the reliability analysis methods were compared to deterministic optimum design results. The reliability based robust optimization using the mean value reliability method showed the most rational results for the probabilistic optimum structure design of the automatic salt collector.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.3
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• pp.454-467
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• 2013

A practical Ship Inner Shell Optimization Method (SISOM), the purpose of which is to improve the safety of the seagoing transport ship by decreasing the maximum Still Water Bending Moment (SWBM) of the hull girder under all typical loading conditions, is presented in this paper. The objective of SISOM is to make the maximum SWBM minimum, and the section areas of the inner shell are taken as optimization variables. The main requirements of the ship performances, such as cargo hold capacity, propeller and rudder immersion, bridge visibility, damage stability and prevention of pollution etc., are taken as constraints. The penalty function method is used in SISOM to change the above nonlinear constraint problem into an unconstrained one, which is then solved by applying the steepest descent method. After optimization, the optimal section area distribution of the inner shell is obtained, and the shape of inner shell is adjusted according to the optimal section area. SISOM is applied to a product oil tanker and a bulk carrier, and the maximum SWBM of the two ships is significantly decreased by changing the shape of inner shell plate slightly. The two examples prove that SISOM is highly efficient and valuable to engineering practice.

• International Journal of CAD/CAM
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• v.9 no.1
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• pp.1-16
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• 2010

When Deterministic Design Optimization (DDO) methods are used, deterministic optimum designs are frequently pushed to the design constraint boundary, leaving little or no room for tolerances (or uncertainties) in design, manufacture, and operating processes. In the Reliability-Based Design Optimization (RBDO) model for robust system design, the mean values of uncertain system variables are usually used as design variables, and the cost is optimized subject to prescribed probabilistic constraints as defined by a nonlinear mathematical programming problem. Therefore, a RBDO solution that reduces the structural weight in uncritical regions does not only provide an improved design but also a higher level of confidence in the design. In this work, we seek to improve the quality of RBDO processes using efficient optimization techniques with object of improving the resulting objective function and satisfying the required constraints. Our recent RBDO developments show its efficiency and applicability in this context. So we present some recent structural engineering applications demonstrate the efficiency of these developed RBDO methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.5
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• pp.1238-1259
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• 2024

Previous studies on joint optimization of computation offloading and service caching policies in Mobile Edge Computing (MEC) have often neglected the impact of dependency-aware subtasks, edge server resource constraints, and multiple users on policy formulation. To remedy this deficiency, this paper proposes a many-objective joint optimization dependency-aware task offloading and service caching model (MaJDTOSC). MaJDTOSC considers the impact of dependencies between subtasks on the joint optimization problem of task offloading and service caching in multi-user, resource-constrained MEC scenarios, and takes the task completion time, energy consumption, subtask hit rate, load variability, and storage resource utilization as optimization objectives. Meanwhile, in order to better solve MaJDTOSC, a many-objective evolutionary algorithm TSMSNSGAIII based on a three-stage mating selection strategy is proposed. Simulation results show that TSMSNSGAIII exhibits an excellent and stable performance in solving MaJDTOSC with different number of users setting and can converge faster. Therefore, it is believed that TSMSNSGAIII can provide appropriate sub-task offloading and service caching strategies in multi-user and resource-constrained MEC scenarios, which can greatly improve the system offloading efficiency and enhance the user experience.

• Journal of the Korea Society of Computer and Information
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• v.9 no.4 s.32
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• pp.117-125
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• 2004

The berth and crane scheduling problem in a container terminal encompasses the whole process of assigning berth to each ship. determining the duration of berthing, assigning container cranes to each ship, and determining the specific start and end time of each crane service, for all the ships scheduled to be arriving at the terminal during a certain scheduling horizon. This problem is basically a constraint satisfaction problem in which all the constraints should be satisfied. However, it is also an optimization problem because the requested arrival and departure time should be met for as many of the scheduled ships as possible. while the operation cost of the terminal should be minimized. In this paper. I present an effective approach to solving this problem, which combines both constraint satisfaction search and iterative improvement search. I test this method on a real world container terminal problem and the results show that the method can produce better results than any other existing method.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.1
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• pp.13-18
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• 2005

This paper considers a design problem of the repetitive control system for linear systems with time-varying norm bounded uncertainties. Using the Lyapunov functional for time-delay systems, a sufficient condition ensuring robust stability of the repetitive control system is derived in terms of an algebraic Riccati inequality (ARI) or a linear matrix inequality (LMI). Based on the derived condition, we show that the repetitive controller design problem can be reformulated as an optimization problem with an LMI constraint on the free parameter.

• Journal of Information Technology Applications and Management
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• v.22 no.2
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• pp.1-17
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• 2015

In this research, we develop and suggest branch and bound algorithms for a two-machine permutation flowshop scheduling problem with the objective of minimizing makespan. In this scheduling problem, after each job is operated on the machine 1 (first machine), the job has to start its second operation on machine 2 (second machine) within its corresponding limited waiting time. In addition, each job has its corresponding ready time at the machine 1. For this scheduling problem, we develop various dominance properties and three lower bounding schemes, which are used for the suggested branch and bound algorithm. In the results of computational tests, the branch and bound algorithms with dominance properties and lower bounding schemes, which are suggested in this paper, can give optimal solution within shorter CPU times than the branch and bound algorithms without those. Therefore, we can say that the suggested dominance properties and lower bounding schemes are efficient.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.3
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• pp.240-245
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• 2005

In this paper, planar waypoint guidance synthesis for UAVs using the LQ optimal impact-angle-control guidance law is proposed. We prove that the energy-optimal control problem with the constraint of passing through the waypoints is equivalent to the problem of finding the optimal pass angles on each waypoint of the optimal impact-angle-control law. The optimal pass angles can be obtained as a numerical solution of the simple pass angle optimization problem that requires neither input parameterization nor constraints. The trajectory obtained by applying the optimal impact-angle-control law with these optimal pass angles becomes energy optimal.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.987-1000
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• 2011

We show how the dynamic optimization problem with the capital constraint can be reduced to the problem to find an optimal modified claim $\tilde{\psi}H$ where $\tilde{\psi}$ is a randomized test in the static problem. Coherent risk measure is used as risk measure in the $L^{\infty}$ random variable spaces. The paper is written in expository style to some degree. We use an average risk of measure(AVaR), which is a special coherent risk measure, to see how to hedge the modified claim in a complete market model.

• Journal of the Korean Operations Research and Management Science Society
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• v.32 no.3
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• pp.17-31
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• 2007

In this paper, we consider a service system with bi-functional servers, which can switch between the primary service room and the secondary room. A service policy is characterized by the switching paints which depend on the queue length in the primary service room and the service level requirement constraint of the secondary room. The primary service room is modeled as a Markovian queueing system and the throughput of the primary service room is function of the total number of bi-functional servers. the buffer capacity of the primary service room, and the service policy. There is a revenue obtained from throughput and costs due to servers and buffers. We study the problem of simuitaneously determining the optimal number of servers, buffer capacity, and service policy to maximize profit of the service system, and develop an algorithm which can be successfully applied with the small number of computations.